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include: Researching, in particular, publicly available data on current and future materials for energy technologies Implementing the materials in our technology database and in our energy system model
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substitution options within the energy system Implementing the phased-out material flows and their substitution options in our technology database and in our energy system model ETHOS.FINE Deriving demand
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/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong electronics background, with experience in design and simulation of analog, digital
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, physics, computer science, mathematics, electrical/electronic engineering or a related subject Strong programming skills (Python) Familiarity with machine learning and deep learning frameworks (e.g
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. Additionally, enjoyment of teamwork is an important requirement. Masters degree in electrical/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong
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, or algorithms to integrate neuromorphic-inspired computing paradigms. Your main tasks will include: Identify areas where neuromorphic-inspired paradigms can be applied Develop concepts to integrate CMOS circuits
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, thermodynamics and practical laboratory work Experience with hydrogen technologies, dehydrogenation reactions, catalysis and partial reforming is advantageous Computational competencies for data analysis and
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, computer science, mathematics or other related subject (you do not need a background in Quantum Computation/Optimization) Good programming skills Useful expertise for the project: Graph Theory/Network
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masters degree and subsequent Ph.D. degree in Computer Science, Mathematics, Physics Engineering or in a similar field. Alternatively an excellent masters degree with professional experience Very good
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Computer Science, Mathematics, Physics Engineering or in a similar field. Alternatively an excellent masters degree with professional experience Very good knowledge and proven skills with larger deep learning